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A comparison of the parameter estimation methods for bimodal mixture Weibull distribution with complete data

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  • Aydin Karakoca
  • Ulku Erisoglu
  • Murat Erisoglu

Abstract

Bimodal mixture Weibull distribution being a special case of mixture Weibull distribution has been used recently as a suitable model for heterogeneous data sets in many practical applications. The bimodal mixture Weibull term represents a mixture of two Weibull distributions. Although many estimation methods have been proposed for the bimodal mixture Weibull distribution, there is not a comprehensive comparison. This paper presents a detailed comparison of five kinds of numerical methods, such as maximum likelihood estimation, least-squares method, method of moments, method of logarithmic moments and percentile method (PM) in terms of several criteria by simulation study. Also parameter estimation methods are applied to real data.

Suggested Citation

  • Aydin Karakoca & Ulku Erisoglu & Murat Erisoglu, 2015. "A comparison of the parameter estimation methods for bimodal mixture Weibull distribution with complete data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(7), pages 1472-1489, July.
    • Handle: RePEc:taf:japsta:v:42:y:2015:i:7:p:1472-1489
    DOI: 10.1080/02664763.2014.1000275
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    Cited by:

    1. Camilo Lillo & Víctor Leiva & Orietta Nicolis & Robert G. Aykroyd, 2018. "L-moments of the Birnbaum–Saunders distribution and its extreme value version: estimation, goodness of fit and application to earthquake data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 45(2), pages 187-209, January.
    2. Muhammet Burak Kılıç & Yusuf Şahin & Melih Burak Koca, 2021. "Genetic algorithm approach with an adaptive search space based on EM algorithm in two-component mixture Weibull parameter estimation," Computational Statistics, Springer, vol. 36(2), pages 1219-1242, June.

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